1. Field of the Invention
The present invention relates to a technique for detecting defects occurring in the manufacture of a semiconductor device, and more particularly, to a method for correcting color variations on the surface of a wafer, a method for selectively detecting defects from different patterns of the wafer, and computer readable recording media for the same.
2. Description of the Related Art
Defects occurring in the manufacture of a semiconductor device greatly affect the reliability and yield of the device, so defect detecting methods are performed at every step of the manufacturing process. According to a general defect detecting method, corresponding pixels of images taken of a wafer in which patterns are repeatedly formed are compared and a pixel having a grey level difference greater than or equal to a threshold value is determined as a defect. Grey level is a measure of brightness on a scale between 0 and 255, where 0 is the dark end of the scale and 255 is the light end of the scale.
A conventional defect detecting method will now be described in greater detail. A wafer surface is irradiated with a light beam emitted from an arbitrary light source. A signal detecting part of a defect detecting apparatus detects light reflected from the wafer surface in pixel units. A grey level value for each of the pixels is determined. A threshold value is set as a reference for defect detection.
For defect detection, the images of three neighboring parts of the wafer surface are compared. Each of the images includes a plurality of pixels. Image B located between Images A and C is a candidate image on which a defect test is to be conducted. Images A and C are reference images serving as a reference for comparison. First, corresponding pixels of Images B and A are compared and grey level differences between the corresponding pixels are calculated. The pixels of Image B that have a grey level difference greater than or equal to a threshold value are identified. Next, corresponding pixels of Images B and C are compared and grey level differences between the corresponding pixels are calculated. The pixels of Image B that have a grey level difference greater than or equal to the threshold value are identified. Only common pixels identified in both comparisons are considered as defects. The most serious problem in the defect detecting method using the above-described image comparison is associated with a metal interconnect process.
FIG. 1 is a photograph of an actual wafer in which metal line patterns 100 and spaces 110 are regularly arranged. As shown in FIG. 1, grains 120 exist in the metal line patterns 100 and a bridge 130 exists in a space 110. Although the grains 120 appear as defects, the grains 120 do not affect the operation of the semiconductor device. However, as shown in FIG. 1, the grains 120 have a grey level value smaller than that of the metal line patterns 110. Thus, in a defect test, the grains 120 are recognized as defects, increasing the total number of defects. As a result, overall process management is adversely affected by the determination of grains as defects.
FIG. 2 is a diagram illustrating an image comparison method when a defect exists in a semiconductor wafer in which metal line patterns 200 and spaces 210 are regularly arranged. In Image B, a bridge 230, which is a fatal defect that seriously affects the yield of semiconductor device, and grains 220 exist. To detect a fatal defect such as the bridge 230, there is a need to increase the sensitivity of the test by reducing the threshold value. However, when the threshold value is set to too small of a value, the grains 220 are also detected as defects, falsely increasing the number of defects. As a result, process management becomes difficult. In contrast, when the threshold value is set to a large value to reduce the sensitivity so that the grains 220 are not detected as defects, there is a problem in that the fatally defective bridge 230 is also not detected.
Meanwhile, another problem of the image comparison method occurs when a wafer being tested has color variations, i.e., when the images of two different parts, e.g., the center and edge, of the wafer have a grey level difference. In FIG. 3, image X represents a relatively dark image taken of the center of the wafer, and image Y represents a relatively bright image taken of the edge of the wafer.
FIGS. 4A and 4B illustrate a defect detecting method using the image comparison method when a wafer has color variations. For a bright image shown in FIG. 4A, the threshold value for defect detection must be set high to detect fewer grains 320, while at the same time, to detect the bridge 330. If the threshold value set based on the bright image is applied to a dark image, as shown in FIG. 4B, there is a problem in that the sensitivity of the defect detection is reduced. In contrast, if the threshold value is set based on the dark image, as shown in FIG. 4B, the grains 320 are also detected in the bright image, as shown in FIG. 4A, so there is a problem in that too many defects are detected.